The hemoglobin, albumin, lymphocyte, and platelet (HALP) is a potent indicator for the prognosis in hemodialysis patients

The hemoglobin, albumin, lymphocyte, and platelet (HALP) values were marked as a original index of general nutritional and inflammatory conditions. The purpose of this investigation was to evaluate the potential relationship between HALP and prognosis in hemodialysis (HD) patients. Patients with maintenance HD from multiple dialysis centers in China were retrospectively analyzed. The primary poor outcome were cardiovascular disease (CVD) and all-cause death. The computational equation of HALP values as the follows: hemoglobin (g/L) × albumin (g/L) × lymphocytes (/L)/ platelets (/L). All participants were divided into Tertile 1, Tertile 2, and Tertile 3 according to the tertiles of baseline HALP values. The Kaplan–Meier curve and the Cox regression was done to figure out the relationship about HALP and adverse outcomes. The restricted cubic splines further identified the possible associations. The time-dependent receiver operating characteristic curve and C-index were implemented for evaluate the predictive values of the HALP composite model. There were 4796 patients incorporate into ultimate study. Compared with patients in Tertile 1, patients in Tertile 3 had an lower risk of all-cause mortality [hazard ratios = 0.66, 95% confidence intervals: 0.49–0.86, P = .007] and CVD mortality [sub-distribution hazard ratio = 0.51, 95% confidence intervals: 0.34–0.80, P = .005]. The composite model with the supplement of HALP outperformed the traditional factor model in the time-dependent receiver operating characteristic curve. High HALP values at baseline are related to a diminished risk of CVD death and all-cause death in HD patients. HALP is a novel and potent index for the prognosis of HD patients.


Introduction
And indeed, hemodialysis (HD) remains the greatest frequent constituent part of kidney replacement therapy in patients with end-stage kidney disease, composing around 89% of overall dialysis and 69% of kidney replacement therapy. Despite continuous innovation in dialysis technology and quality of care, the burden of symptoms, economics and mortality remains grave, notably in low and middle-income countries. Essentially 67% of HD dialysis is influenced by cardiovascular disease (CVD), accounting for nearly 50% of mortality, and is the key content of standardized outcomes in nephrology-HD. [1,2] Previous studies have proved that immune disorders, chronic inflammation and nutritional deficiencies are important risk factors leading to adverse outcomes of patients, which are intimately related to the occurrence of CVD matters and allcause death. [3,4] However, the commonly used clinical prognostic indicators have not been fully verified (such as blood phosphorus level, blood calcium level, weekly adequacy of dialysis, hemoglobin, micro-inflammatory biomarkers, and oxidative stress). [5,6] Studies have reported that these indicators are related to poor outcomes of HD patients, but there are large differences in these studies. The single index has low predictive ability and 1-sided reflection of body characteristics. Finding a unified definition, convenient collection, and comprehensive reporting of evaluation systems is essential to ameliorate the survival in HD patients.
The hemoglobin, albumin, lymphocyte, and platelet (HALP) composite values were acknowledged as a original index of general nutritional and inflammation condition. [7,8] and has recently Medicine been identified as bladder cancer, breast cancer, acute heart failure, acute ischemic stroke, and other important prognostic factors in patients. [9][10][11][12][13] Nevertheless, it is indefinite if HALP values are correlated with prognosis in HD patients, and our work aimed to determine the association of HALP with all-cause mortality and CVD mortality.

Subjects
Research participants were collected from the clinical database of dialysis and follow-up in 4 large hemodialysis centers in China, which is located on the website of Chinese national renal data system (www.cnrds.net). In this study, we retrospectively analyzed the patients with maintenance HD over 18 years of age and dialysis duration more than 3 months from January 2008 to October 2022. The baseline period for inclusion was 1 week before the start of dialysis. The exclusion criteria were as follows: Have been recent invasive operations except surgery for dialysis access; With acute infection, autoimmune disease, malignant tumor or hemopathy; The use of anti-inflammatory, antiplatelet or immunosuppressive drugs; Missing essential baseline data such as blood cell count and serum albumin; and Without outcome data. The Ethics Review Committee approved the study programme (JJSDYYMYY-YXLL-2022-108), and the patient's informed consent form was exempted because it was a retrospective data analysis and there was no individual identification information.

General data
Demographic and clinical factors included age, gender, body mass index, smoking status, comorbidities (including diabetes, hypertension and past history of CVD), and common drug use during the baseline period of the analysis. Laboratory values included blood cell count (hemoglobin, neutrophil count, lymphocyte count, monocyte count, platelet count), biochemical indicators (alanine transaminase, aspartate transaminase, albumin, blood lipids, uric acid, serum creatinine, estimated glomerular filtration rate (eGFR), blood calcium, blood phosphorus), intact parathormone (iPTH) and C-reactive protein (CRP).

HALP
The baseline blood count data was used to evaluate the markers needed for the study. The computational equation of HALP values as the follows: hemoglobin (g/L) × albumin (g/L) × lymphocytes (/L)/platelets (/L).

Clinical end points
The end points measure of the study were CVD death and all-cause death. CVD death included cardiac failure, coronary heart disease, pulmonary edema, stroke, arrhythmia, and other fatal CVD status. The determination of cause of death was obtained after a clinical case discussion.

Statistical processing
The conforming to normal distributions were displayed as mean ± standard deviation, while skewed distributions were expressed as median (interquartile range: P25, P75). Classification data were shown as frequency (n) and percentage (%). Derived from the tertiles of baseline HALP values, the object of observation was chopped up into 3 groups: Tertile 1, Tertile 2, and Tertile 3. The cumulative risk of death in the baseline HALP values were determined by the Kaplan-Meier curve and log-rank analysis. The Cox regression was done to figure out the risk of adverse outcomes in the ternary of HALP. Frequently reported confounding factors that involved in the causes of CVD and all-cause death for HD were considered to be potential covariates. Time-dependent receiver operating characteristic curve and C-index were conducted in estimate the prognostic value about HALP and compared with traditional factors. Besides, we implemented restricted cubic splines to study the potential nonlinear relationship between HALP continuous variables with the hazard of all-cause mortality. R software (www.r-project.org) was applied to analyze in this research. Significance was defined at P value < .05.

Baseline characteristics
We selected 5883 participants and finally analyzed the available population data of 4796. The flow map was shown in Figure 1. The average age of all patients was 55.8 ± 12.3 years old, including 2226 (46.4%) males and 2570 (53.6%) females. The baseline HALP values were 26.4 (17.1, 35.2). According to Table 1 Comparison of general baseline data in different groups of hemoglobin, albumin, lymphocyte, and platelet (HALP). .      the baseline data range, the subjects were divided into 3 groups: Tertile 1 (<20.3, n = 1599), Tertile 2 (≥20.3, ≤31.6, n = 1599) and Tertile 3 (<31.6, n = 1598). The results indicated that: in contrasted to patients with increased HALP, patients with decrease HALP had older age, more diabetes and a higher proportion of previous history of CVD; lower lymphocyte count, monocyte count, hemoglobin, albumin, and calcium levels; higher neutrophil count, platelet count, blood phosphorus and CRP levels; and other demographic characteristics and clinic parameters of the participants were shown in Table 1.

Correlation between HALP and poor prognosis
The mean follow-up time of whole participants was 65 (interquartile range: 36, 96) months, and 1907 patients died at the end of follow-up, of which 1024 (53.6%) died from CVD. The results of Kaplan-Meier survival curve were demonstrated that the overall survival rate of patients in Tertile 3 of HALP was dramatically lower than that in Tertiles 1 and 2 (Log-rank test χ2 = 62.4, P < .001). (Fig. 2).
Further analysis, the results of Fine-Gray competitive risk model revealed that the decrease of HALP was also related to the increase of CVD mortality (Gray = 33.94, P < .001) (Fig. 4). The corrected CVD death risk ratio of the Tertile 3 of HALP is significantly lower than that of the Tertile 1 (sub-distribution hazard ratio = 0.51, 95% CI: 0.34-0.80, P = .005) ( Table 3).
Meanwhile, the multivariate adjusted restricted cubic splines revealed that there was a linear correlation between HALP and all-cause death in HD (P for non-linearity = 0.436), showing a trend that the dwindle HALP the more advanced hazard of death (Fig. 5).

The forecast value of HALP for mortality
The combination of previously obtained factors (age, history of CVD, diabetes, and eGFR) affecting the prognosis of all-cause mortality and common controversial HD risk factors (gender, smoking, β-blocker, statins, erythropoiesis stimulating agents, hypertension, total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, CRP, calcium, phosphate, and iPTH) was named the traditional factors model, when the HALP was added to this model, named the traditional factors + HALP model. Time-dependent receiver operating characteristic curve analysis exhibited that the area under curve of the traditional factors model for all-cause mortality was 0.641 at 1 year, 0.689 at 3 years, and 0.693 at 5 years, while the traditional factors + HALP model was 0.687 at 1 year, 0.752 at 3 years, and 0.763 at 5 years, all P < .001 (Fig. 6).

Discussion
The source of this research was a multi-center with a long follow-up period and a large sample of database. To our knowledge, this was a initial finding that decreased baseline HALP values were distinctly correlated with inferior outcome under HD (cubic spline curves indicated a negative linear relationship with risk of all-cause death). Multiple statistical analyses of study confirmed high risk for CVD and all-cause mortality as well. Cox analysis revealed an isolated association between HALP and undesirable outcome, after adjusting for multiple covariates, indicating that it was independent of traditional risk factors (according to the HALP tertiles, patients with the lowest score had a 34% increased risk of all-cause death relative to the highest, after adjustment). Additionally, we have validated that adding HALP values to traditional risk factor models could boost the forecast competence of all-cause mortality. In brief, Table 3 Sub-distribution hazard ratio (SHR) about hemoglobin, albumin, lymphocyte, and platelet (HALP) and cardiovascular disease (CVD) mortality. Model 1: was adjusted for age, gender, smoking, β-blocker, statins, ESAs, history of cardiovascular disease, hypertension and diabetes. Model 2: was adjusted for Model 1 + clinic factors (body mass index, blood lipid, uric acid, estimated glomerular filtration rate, calcium, phosphate, intact parathyroid hormone and C-reactive protein). CI = confidence intervals, ESAs = erythropoiesis stimulating agents, SHR = sub-distribution hazard ratio. this data was presented to demonstrate that dwindle HALP values could be a risk factor for poor prognosis in HD patients.
Previous studies have point out that nutrition and inflammatory are convincingly related to the outcomes of HD patients. [14,15] Anemia can contribute to ventricular hypertrophy, aggravating heart failure and myocardial ischemia, resulting in low immunity, increasing infection and other adverse complications, and connecting with the occurrence of CVD events ultimately, low quality of life, cognitive impairment and mortality. [16] Hypoalbuminemia is a manifestation of malnutrition, which weakens the immune response and makes infection more likely and also associated with inflammation in the body. [17] Inflammation can trigger embolism, where platelets involved in conglutination, enhanced reaction and polymerization. Simultaneously, in the process of inflammation clearance and ameliorating, immune cells play a significant role. [18] Researches have found that high platelet-lymphocyte ratio is associated with arteriovenous fistula stenosis and thrombosis in HD patients. [19] In consequence, HALP has a strong biological basis as an indicator integrating the interactions between nutrition, inflammation, platelet function, and immune function.
Based on the calculation formula of HALP, lower values means more potential inflammation, poorer immune response, higher risk of blood clots, and more severe malnutrition. At the same time, through the data of this study, it was found that lower HALP also seemed to be concerned in hypocalcemia and hyperphosphatemia, which are the manifestations of chronic kidney disease-mineral and bone disorder. [20] Therefore, it makes sense that low HALP has relation to a poor prognosis in HD.
In fact, recently, it has been reported that HALP can indicate the malnutrition and systemic inflammatory state of chronic diseases, and it turns out to be a relevant outcome symbol for different tumors. [9][10][11][12][13] Interestingly, there are some improved indicators based on blood laboratory tests, such as Neutrophil-Lymphocyte Ratio and Monocyte-lymphocyte ratio, [21,22] which are often mentioned in the analysis of the appraisal of nutritional and inflammatory condition in dialysis subjects.
Among the traditional prognostic factors of HD, there are often inconsistent conclusions about eGFR, calcium, phosphorus, and iPTH. It is a simple utility that CRP or lipid variables reflect the body, while β-blockers, CVD history, and diabetes are closely related to the patient's past history and fail to highlight the characteristics of hemodialysis. Micro-inflammatory factors, such as tumor necrosis factor-α or interleukin-6, cannot be routinely measured. However, the HALP is a simple, effective and low-cost assessment indicator for a more comprehensive assessment of the inflammatory-nutritional status of HD patients. When used alone, it can reflect the inflammation-nutritional status of patients and predict the poor prognosis of HD patients, while combined with traditional risk factors, this effect was significantly increased.
There were some inadequacies in our work. Primarily, as a retrospective research, election bias was inevitable and causality could not be clearly defined at this stage. Secondly, although there were many confounding factors included in correction, dynamic factors such as detailed drug prescription changes, maintenance of dialysis vascular access, and fluctuations in dialysis adequacy could not be completely analyzed due to incomplete data. Ultimately, the optimal diagnostic HALP values remain unclear. Traditional factors = age, gender, smoking, β-blocker, statins, ESAs, history of cardiovascular disease, hypertension and diabetes, total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, C-reactive protein, calcium, phosphate, intact parathyroid hormone and estimated glomerular filtration rate. CI = confidence intervals, ESAs = erythropoiesis stimulating agents, HALP = hemoglobin, albumin, lymphocyte, and platelet, IDI = integrated discrimination improvement, NRI = net reclassification improvement. Consequently, deeper prospective studies are necessary to validate the results thoroughly in following investigation.

Conclusion
Our analysis demonstrated a negative association between baseline HALP and risk of all-cause death and CVD death in HD patients, suggesting that HALP values before dialysis may be a reliable indicator of poor prognosis.